Incorporating Colour Information for Computer-Aided Diagnosis of Melanoma from Dermoscopy Images: A Retrospective Survey and Critical Analysis

IF 3.3 Q2 ENGINEERING, BIOMEDICAL
Ali Madooei, M. S. Drew
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引用次数: 23

Abstract

Cutaneous melanoma is the most life-threatening form of skin cancer. Although advanced melanoma is often considered as incurable, if detected and excised early, the prognosis is promising. Today, clinicians use computer vision in an increasing number of applications to aid early detection of melanoma through dermatological image analysis (dermoscopy images, in particular). Colour assessment is essential for the clinical diagnosis of skin cancers. Due to this diagnostic importance, many studies have either focused on or employed colour features as a constituent part of their skin lesion analysis systems. These studies range from using low-level colour features, such as simple statistical measures of colours occurring in the lesion, to availing themselves of high-level semantic features such as the presence of blue-white veil, globules, or colour variegation in the lesion. This paper provides a retrospective survey and critical analysis of contributions in this research direction.
结合皮肤镜图像中黑色素瘤计算机辅助诊断的颜色信息:回顾性调查和批判性分析
皮肤黑色素瘤是最危及生命的皮肤癌。虽然晚期黑色素瘤通常被认为是无法治愈的,但如果及早发现并切除,预后是有希望的。今天,临床医生在越来越多的应用中使用计算机视觉,通过皮肤图像分析(特别是皮肤镜图像)来帮助早期发现黑色素瘤。肤色评估对皮肤癌的临床诊断至关重要。由于这种诊断的重要性,许多研究要么关注或使用颜色特征作为其皮肤病变分析系统的组成部分。这些研究的范围从使用低级的颜色特征,如病变中发生的颜色的简单统计测量,到利用自己的高级语义特征,如病变中存在的蓝白色面纱、球体或颜色变化。本文对这一研究方向的贡献进行了回顾性调查和批判性分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
12.00
自引率
0.00%
发文量
11
审稿时长
20 weeks
期刊介绍: The International Journal of Biomedical Imaging is managed by a board of editors comprising internationally renowned active researchers. The journal is freely accessible online and also offered for purchase in print format. It employs a web-based review system to ensure swift turnaround times while maintaining high standards. In addition to regular issues, special issues are organized by guest editors. The subject areas covered include (but are not limited to): Digital radiography and tomosynthesis X-ray computed tomography (CT) Magnetic resonance imaging (MRI) Single photon emission computed tomography (SPECT) Positron emission tomography (PET) Ultrasound imaging Diffuse optical tomography, coherence, fluorescence, bioluminescence tomography, impedance tomography Neutron imaging for biomedical applications Magnetic and optical spectroscopy, and optical biopsy Optical, electron, scanning tunneling/atomic force microscopy Small animal imaging Functional, cellular, and molecular imaging Imaging assays for screening and molecular analysis Microarray image analysis and bioinformatics Emerging biomedical imaging techniques Imaging modality fusion Biomedical imaging instrumentation Biomedical image processing, pattern recognition, and analysis Biomedical image visualization, compression, transmission, and storage Imaging and modeling related to systems biology and systems biomedicine Applied mathematics, applied physics, and chemistry related to biomedical imaging Grid-enabling technology for biomedical imaging and informatics
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